The need for locating a mobile device or its user may come from the user desiring to know one's own location or from an authority for which the information about the location of a person has become important for some reason, e.g., in a case of emergency.
Location tracking devices and other such mobile terminals, e.g. smartphones or other hand-held or wearable apparatuses, may comprise cellular communication functionality such as a transceiver for collecting cellular data from nearby cells/base stations, e.g. indications of signal strength, and reporting it to a receiver at the remote location, and most typically, a satellite-based location determination functionality, e.g. a receiver and related positioning logic for global positioning system (GPS) or GLONASS (Global Navigation Satellite System) satellite positioning signals.
To determine a location based on utilizing a satellite signal such as the GPS signal, a GPS receiver must have current almanac data and ephemeris data from at least three appropriate satellites and an initial estimate of its location. However, the associated signal coverage easily suffers from interruptions caused by landscape obstructions such as geographic features, buildings or related urban canyon, trees, etc. Because mobile devices are often operated in positioning-wise challenging environments, such as cities and urban areas, wherein GPS or generally satellite navigation signal reception will be intermittent, this can result in poor performance of the location tracking system based thereon.
There are some supplementary technologies developed to tackle the weaknesses of GPS-based existing location determination technology at location tracking devices such as GPS-equipped mobile terminals. One proposed method is assisted GPS (AGPS) to update the almanac and/or ephemeris data in order to improve performance of the associated devices. AGPS systems exploit remote terrestrial stations in locations in which good reception of satellite signals is expected and assistance data established based on signals received thereat are then transmitted e.g. via a cellular communication network to the mobile terminals.
The start-up of a GPS-receiver typically requires the initial estimate of its location and this process takes several minutes. In order to speed up the start-up of the GPS-receiver, the remote/mobile terrestrial stations can produce assistance data based on identifiers of cellular network base stations and time delay data received from the cellular network base stations, and this data is used to improve the initial location estimate.
The location estimation procedure described above takes into account assistance data that includes ephemeris data received from satellites and identifier and time delay data from the cellular base stations. Despite of its obvious benefits in certain use scenarios, it may also easily result in inaccurate location estimate because certain environment obstructions and their influences are ignored during the process. The location estimation described above is based on performing an analysis of the location of the mobile terminal with respect to the locations of the base stations and therefore if the exact base station locations are not available the resulting location estimates become distorted. The location estimation procedures described above do not estimate for each cell a location of a base station or a coverage area of the base station (area reached by the radio signal). Yet, the location estimation procedures described above don't make any estimation of a type of the cell with regard to landscape and cityscape, etc.
WO 2010/055192 discloses a method and system for positioning with enhanced accuracy. The suggested solution yields excellent results based on first collecting, from a number of terminals devices, positioning data such as GPS data and environment data including e.g. cell data during a modelling phase to determine covered area estimates of cell network base stations, whereupon during a locating phase the mere environment data suffices for accurate positioning due to the available covered area estimates with various supplementary data.
In US 2013/0079039, the solution of '192 is developed further by adding vertical information to the position estimates to obtain true 3D (three dimensional) positioning.
Notwithstanding the numerous improvements the '192 and '039 clearly introduce to the prior art, the associated solutions may still be optimized having regard to a number of factors and different possible use scenarios.
Yet, as the information available about the environment of an object, such as a mobile phone, to be tracked becomes all the time more versatile due to the emerge of new communications technologies such as 4G/LTE (Fourth Generation/Long-Term Evolution) or 5G (Fifth Generation mobile networks), also new possibilities may arise to extend the data input space. By concentrating the locating efforts around any certain, single type of data source or a related model may not give optimum results during real-time positioning, when a variety of data sources in terms of different network signals, etc. are available and detectable by the object to be positioned.
Further, many of the contemporary positioning solutions work lousily in situations where data input space used for locating a target device is at least momentarily and e.g. abruptly reduced or severely distorted, whereupon a position estimates solely based on the latest data input is easily very erroneous. These solutions greatly omit the potentially massive data history collected earlier and information derivable therefrom to maintaining the positioning accuracy also in changing conditions with poor signal reception.
Based on the above-mentioned, it is clear that the locating of mobile devices can still further be developed. Especially techniques which do not require satellite positioning or prior knowledge of the locations of base stations or wireless network access points are needed.